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Facial expression recognition under occlusion conditions based on multi-feature cross-attention

Journal of intelligent and Fuzzy systems 2024年第4期46卷 9841-9856页

作者： Guo, Sheng Tan, Mian Cai, Shan Zhang, Zaijun Liang, Yihui Feng, Hongxi Zou, Xue Wang, Lin School of Data Science and Information Engineering Guizhou Key Laboratory of Pattern Recognition and Intelligent System Guizhou Minzu University Guiyang China School of Mathematics and Statistics Qiannan Normal University for Nationalities Key Laboratory of Complex Systems and Intelligent Optimization of Guizhou Province Duyun China Zhongshan Institute University of Electronic Science and Technology of China Zhongshan China Guizhou Aerospace Tianma Electromechanical Technology Co LTD Zunyi China

Although facial expression recognition (FER) has a wide range of applications, it may be difficult to achieve under local occlusion conditions which may result in the loss of valuable expression features. This issue has motivated the present study, as a part of which an effective multi-feature cross-attention network (MFCA-Net) is proposed. The MFCA-Net consists of a two-branch network comprising a multi-feature convolution module and a local cross-attention module. Thus, it enables decomposition of facial features into multiple sub-features by the multi-feature convolution module to reduce the impact of local occlusion on facial expression feature extraction. In the next step, the local cross-attention module distinguishes between occluded and unoccluded sub-features and focuses on the latter to facilitate FER. When the MFCA-Net performance is evaluated by applying it to three public large-scale datasets (RAF-DB, FERPlus, and AffectNet), the experimental results confirm its good robustness. Further validation is performed on a real FER dataset with local occlusion of the face. © 2024 – IOS Press.

关键词： Convolution

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Improved Time Position Estimation of Manet UAV Routing Protocol 6

Improved Time Position Estimation of Manet UAV Routing Proto...

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6th International Conference on Signal and Image Processing, ICSIP 2021

作者： Mbyamm Kiki, Mesmin J. Iddi, Ibrahim Yunusa, Haruna Beihang University School of Electronic and Information Engineering Beijing China Beihang University School of Pattern Recognition and Intelligent Systems Beijing China

ISBN: (纸本)9780738133737

With routing protocols that are primarily concerned with location estimates, the most significant problem is that new neighbors are acquired slowly, which results in inefficient routing decisions. Because routing and forwarding would fail if the next-hop unmanned aerial vehicle (UAV) was no longer in sight. In this paper a system that makes use of unscented Kalman filter prediction in response to improve the next-hop position in real time in order to reduce the overall performance of route forwarding is proposed. It is being introduced to the classic GPRS protocol in order to facilitate the development of new routing protocols with OPNET. The new routing protocol demonstrates a greater rise in point-to-point packet delay and forwarding rate when compared to the original routing system. © 2021 IEEE.

关键词： Kalman filters

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Improved AOMDV Routing Protocol in Manet UAV Based on Virtual Hop 3

Improved AOMDV Routing Protocol in Manet UAV Based on Virtua...

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3rd International Conference on Computer Communication and the Internet, ICCCI 2021

作者： Kiki, Mesmin J. Mbyamm Iddi, Ibrahim Yunusa, Haruna School of Electronic and Information Engineering Beihang University Beijing China School of Pattern Recognition and Intelligent Systems Beihang University Beijing China

ISBN: (纸本)9781728176185

In order to improve the load balancing capability of the AOMDV routing protocol of the ad hoc network, the network nodes are divided into two levels, Risk and No risk, based on the queue buffer ratio, and a different processing is done for different levels. Directly remove the risk level nodes and assign the corresponding virtual hops to the No Risk level nodes via the threshold comparison. The higher the queue cache rate, the higher the corresponding virtual hops. The RREP and Hello messages are expanded, and the node queue cache ratio is added to update and collect the latest path node status information. The improved protocol uses the minimum virtual hops containing node load information as the basis for optimal path selection, and uses OPNET to simulate at a fixed node rate under different network loads. The results show that the improved routing protocol plays a role in load balancing for nodes at the expense of limited routing overhead, relieves network congestion, increases the packet delivery rate, effectively reduces the end-to-end transmission delay, and improves self-organization. Network performance provides a relatively simple method. © 2021 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Ant Colony Implementation on AODV Routing Protocol

Ant Colony Implementation on AODV Routing Protocol

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2021 IEEE International Conference on Advances in Electrical Engineering and Computer Applications, AEECA 2021

作者： Mbyamm Kiki, Mesmin J. Iddi, Ibrahim Yunusa, Haruna School of Electronic and Information Engineering Beihang University Beijing China School of Pattern Recognition and Intelligent Systems Beihang University Beijing China

ISBN: (纸本)9781665435611

Wireless Ad Hoc Network Routing developed on demand-based distance vector (AODV) is a routing protocol whose characteristic is that distance is the vector. This paper introduces the development process of the protocol;enumerate the routing table entries of the AODV protocol and basic undertaking operations in the protocol. It shows that keeping specific state information in routing table entries can correctly establish peer nodes. Also, according to the related issue that has to be considered in the deployment, it is proposed that the ant colony algorithm and the AODV protocol should complement each other. The ant colony algorithm has been applied to solve the problem of small storage capacity of a single node in the protocol, energy loss caused by frequent topological changes, and time delay caused by unstable communication media. © 2021 IEEE.

关键词： Routing protocols

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Gait Planning and Motion Control Based on Vrep Simulation for Quadruped Robot 5

Gait Planning and Motion Control Based on Vrep Simulation fo...

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5th World Robot Conference Symposium on Advanced Robotics and Automation, WRC SARA 2023

作者： Zhou, Linqi Chen, Zhihua Liu, Jun Liu, Zhi Chen, Yumeng Zhang, Liting Nanchang Hangkong University Key Laboratory of Jiangxi Province for Image Processing and Pattern Recognition Moe Key Lab of Nondestructive Testing Technology Nanchang330063 China Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing100081 China

ISBN: (纸本)9798350307320

Gait planning of quadruped robots plays an important role in achieving less walking, including dynamic and static gait. In this article, a static and dynamic gait control method based on center of gravity stability margin is proposed. Firstly, the robot model and kinematics modeling are introduced. Secondly, the robot's foot static and dynamic gait were planned and the foot trajectory was designed. Finally, two types of gait of the robot were simulated using Vrep simulation software, and the differences in stability and speed between the coordinated gait with speed and stability in the static and dynamic gait of a 12 degree of freedom robot were analyzed, verifying the effectiveness of the gait control method proposed in this paper. © 2023 IEEE.

关键词： Robot programming

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Autonomous Obstacle Avoidance Scheme Using Monocular Vision Applied to Mobile Robots

Autonomous Obstacle Avoidance Scheme Using Monocular Vision ...

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2020 International Conference on intelligent Control, Measurement and Signal Processing and intelligent Oil Field, ICMSP 2020

作者： Song, Yun Yun Yang, Sheng Yi Liu, Chao Wu, Qing Gui School of Data Science and Information Engineering Key Laboratory of Pattern Recognition and Intelligent Systems of Guizhou Province Guizhou Minzu University Guiyang China School of Mechatronics Engineering Guizhou Minzu University Guiyang China

Mobile robots cannot move in an unknown environment with static or slow-moving obstacles effectively. We present an enhanced obstacle avoidance strategy using monocular vision to solve this problem. First, we combine Canny and Otsu to extract the barrier feature and find the critical pixel position of obstacles by the monocular vision. Then the image depth estimation algorithm is used to estimate the gaps. With these parameters of barriers, an improved bug algorithm is proposed to avoid the obstacles autonomously. The experiments show that the proposed obstacles avoidance strategy can effectively make a small mobile robot avoid different kinds of obstacles. © Published under licence by IOP Publishing Ltd.

关键词： Mobile robots

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Zero-Shot Audio Captioning Using Soft and Hard Prompts

IEEE Transactions on Audio, Speech and Language Processing

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IEEE Transactions on Audio, Speech and Language Processing 2025年 33卷 2045-2058页

作者： Yiming Zhang Xuenan Xu Ruoyi Du Haohe Liu Yuan Dong Zheng-Hua Tan Wenwu Wang Zhanyu Ma Pattern Recognition and Intelligent System Laboratory School of Artificial Intelligence Beijing University of Posts and Telecommunications Beijing China Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China Centre for Vision Speech and Signal Processing University of Surrey Guildford U.K. Department of Electronic Systems Aalborg University Aalborg Denmark

In traditional audio captioning methods, a model is usually trained in a fully supervised manner using a human-annotated dataset containing audio-text pairs and then evaluated on the test set from the same dataset. Such methods have two limitations. First, these methods are often data-hungry and require time-consuming and expensive human annotations to obtain audio-text pairs. Second, these models often suffer from performance degradation in cross-domain scenarios, i.e., when the input audio comes from a different domain than the training set, and this issue has received little attention. To address these issues, we propose a new zero-shot method for audio captioning. Our method is built on the contrastive language-audio pre-training (CLAP) model. During training, the model reconstructs the ground-truth caption using the CLAP text encoder. In the inference stage, the model generates text descriptions from the CLAP audio embeddings of given audio inputs. To enhance the ability of the model in transitioning from text-to-text generation to audio-to-text generation, we propose to use the mixed-augmentations-based soft prompt to learn more robust latent representations, leveraging instance replacement and embedding augmentation. Additionally, we introduce the retrieval-based acoustic-aware hard prompt to improve the cross-domain performance of the model by employing the domain-agnostic label information of sound events. Extensive experiments on AudioCaps and Clotho benchmarks show the effectiveness of our proposed method, which outperforms other zero-shot audio captioning approaches for in-domain scenarios and outperforms the compared methods for cross-domain scenarios, underscoring the generalization ability of our method.

关键词： Training Decoding Semantics Data models Acoustics Electronic mail Benchmark testing Transformers Robustness Perturbation methods

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GeoPix: Multi-Modal Large Language Model for Pixel-level Image Understanding in Remote Sensing

arXiv

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arXiv 2025年

作者： Ou, Ruizhe Hu, Yuan Zhang, Fan Chen, Jiaxin Liu, Yu Pattern Recognition and Intelligent System Lab School of Artificial Intelligence Beijing University of Posts and Telecommunications Beijing100876 China Institute of Remote Sensing and Geographic Information Systems School of Earth and Space Sciences Peking University Beijing100871 China Peking University Ordos Research Institute of Energy Ordos017000 China

Multi-modal large language models (MLLMs) have achieved remarkable success in image- and region-level remote sensing (RS) image understanding tasks, such as image captioning, visual question answering, and visual grounding. However, existing RS MLLMs lack the pixel-level dialogue capability, which involves responding to user instructions with segmentation masks for specific instances. In this paper, we propose GeoPix, a RS MLLM that extends image understanding capabilities to the pixel level. This is achieved by equipping the MLLM with a mask predictor, which transforms visual features from the vision encoder into masks conditioned on the LLM’s segmentation token embeddings. To facilitate the segmentation of multi-scale objects in RS imagery, a class-wise learnable memory module is integrated into the mask predictor to capture and store class-wise geo-context at the instance level across the entire dataset. In addition, to address the absence of large-scale datasets for training pixel-level RS MLLMs, we construct the GeoPixInstruct dataset, comprising 65,463 images and 140,412 instances, with each instance annotated with text descriptions, bounding boxes, and masks. Furthermore, we develop a two-stage training strategy to balance the distinct requirements of text generation and masks prediction in multi-modal multi-task optimization. Extensive experiments verify the effectiveness and superiority of GeoPix in pixel-level segmentation tasks, while also maintaining competitive performance in image- and region-level benchmarks. The models, dataset, and code are publicly available at https://***/Norman-Ou/GeoPix. © 2025, CC BY.

关键词： Image segmentation

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Improved RRT algorithm path planning combined with artificial potential field algorithm 11

Improved RRT algorithm path planning combined with artificia...

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2021 11th International Workshop on Computer Science and Engineering, WCSE 2021

作者： Wang, Xiufen Yang, Shengyi School of Mechanical Electronic Engineering Guizhou Minzu University Guizhou Guiyang550025 China Key Laboratory of Pattern Recognition and Intelligent Systems of Guizhou Province Guizhou Minzu University Guizhou Guiyang550025 China

ISBN: (纸本)9789811817915

In order to solve the problem of low path planning efficiency in complex obstacle environment, an improved Rapidly-exploring Random Trees (RRT) algorithm is proposed. It utilizes artificial potential field to guide the fast expanding random tree to growing towards the target and away from obstacles. Considering the gravitational field of the target node and the repulsion field of the obstacle in the artificial potential field, a certain number of random nodes generated in one iteration are evaluated and selected. The simulation results show that the improved RRT algorithm has strong advantages over the basic RRT algorithm in search ability and computation time. © 2021 11th International Workshop on Computer Science and Engineering, WCSE 2021. All Rights Reserved.

关键词： Motion planning

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Interval Type-2 Enhanced Possibilistic Fuzzy C-Means Noisy Image Segmentation Algorithm Amalgamating Weighted Local Information

SSRN

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SSRN 2024年

作者： Huang, Chengquan Lei, Huan Chen, Yang Cai, Jianghai Qin, Xiaosu Peng, Jialei Zhou, Lihua Zheng, Lan Engineering Training Center Guizhou Minzu University Guiyang550025 China School of Data Science and Information Engineering Guizhou Minzu University Guiyang550025 China Key Laboratory of Pattern Recognition and Intelligent Systems of Guizhou Province Guizhou Minzu University Guiyang550025 China

The fuzzy clustering algorithms based on interval type-2 are effective methods for data clustering and image segmentation with some potential advantages in dealing with higher-order uncertainty. However, the fuzzy clustering algorithms based on interval type-2 have limited accuracy in noisy image segmentation. Therefore, we propose a new noisy image segmentation algorithm based on weighted local information for interval type-2 enhanced possibilistic fuzzy C-means clustering. Firstly, a new possibilistic fuzzy weighted local information factor, which amalgamates the mutually guided image filtering, is devised to control the relationship between mutually guided image filtering and the original image utilizing the absolute difference image between the original image and mutually guided image filtering. Additionally, two weighted sum functions are also introduced into the new possibilistic fuzzy weighted local information factor to calculate the greyscale differences between the current pixel and its neighborhood pixels. Secondly, the distance of the objective function is corrected using mutually guided image filtering to obtain the local features and global information of the image. Finally, this paper introduces the new possibilistic fuzzy weighted local information factor into the interval type-2 possibilistic fuzzy C-means clustering algorithm and proposes a new interval type-2 enhanced possibilistic fuzzy C-means clustering algorithm with local information and mutually guided image filtering constraints to improve noisy image segmentation results. Through extensive experiments on noisy synthetic images and noisy real images, the proposed algorithm can achieve higher performance and more accurate segmentation results compared with several existing algorithms. © 2024, The Authors. All rights reserved.

关键词： Image segmentation

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